System for evaluating relevance between persons

ABSTRACT

Embodiments herein properly determine relevance between persons. Embodiments herein provide a system for evaluating relevance between persons, including relevance detecting means for detecting directed relevance of a person as a target to another person based on a text in which evaluations or feelings of the other person by another person is expressed; storing means for storing the detected relevance; evaluating means for evaluating, with respect to a set of a first person and second person to be evaluated, relevance between the first person and the second person based on a plurality of relevances including the stored relevances and reaching the second person from the first person via at least one further person; and outputting means for outputting the relevance evaluated.

FIELD OF THE INVENTION

The present invention relates to a system for evaluating relevancebetween persons. More specifically, the present invention relates to asystem for evaluating relevance between persons based on the descriptionof a text.

BACKGROUND OF THE INVENTION

In a marketing strategy for products and services, the acquaintancerelation between persons sometimes referred to as personal connection orhuman network may become important. For example, when it is desired thata product or a service is purchased by a person, it is effective to haveanother person, who is trusted by that person, recommend to purchase theproduct or the service. However, acquaintance relation is not simple,and it is difficult to know a possibility that the most effective resultis obtained when who gets an introduction from whom.

Conventionally, there has been proposed a technique graphicallydisplaying relevance between persons, as a reference technique (refer toPatent Document 1). However, according to this technique, providing therelevance between persons is effected by whether a plurality of names ofpersons are described in the same electronic data (text, for example) ornot. Also, a node indicating a person is connected to a node indicatinga person who is related to the former person by an edge. A graph createdby repeating these connections is displayed for user.

-   -   [Patent Document 1] Japanese Unexamined Patent Publication        (Kokai) No. 2005-108123.

SUMMARY OF THE INVENTION

However, the graph created by the above-mentioned reference technique isan undirected graph composed of undirected edges. Therefore, this graphcannot express a situation in which a person unilaterally respectsanother person or a situation in which a person highly appreciates apersonality of another person unilaterally. Therefore, it is difficultto utilize this technique in a practical application such as autilization for a marketing strategy.

Further, even in the case where two persons are described in the commontext, there is a possibility that the two persons are in a competitiverelation or have feelings of dislike with each other. In such a case,the use of the acquaintance relation for a market strategy may have anadverse effect. In this way, in the prior art, it is difficult toutilize the acquaintance relation expressed by the graph in a practicalapplication such as a marketing strategy.

Therefore, the object of the present invention is to provide a system, amethod, and a program which can solve the above-mentioned problems. Thisobject is attained by the combinations of features described inindependent claims in the scope of claims. Also, dependent claims definefurther advantageous specific embodiment.

For solving the above problem, the present invention provides a systemfor evaluating relevance between persons, including:

-   -   detecting means for detecting directed relevance of a person as        a target to another person based on a text in which evaluations        or feelings of the person by another person are expressed;    -   storing means for storing the detected relevance;    -   evaluating means for evaluating, with respect to a set of a        first person and a second person to be evaluated, relevance        between the first person and the second person based on a        plurality of relevances including the detected relevances and        reaching the second person from the first person via at least        one further person; and    -   outputting means for outputting the evaluated relevance.

The concept of the present invention is not the enumeration of all thenecessary features of the present invention, but subcombinations of thefeatures thereof may be also accepted as the inventions.

According to the present invention, the relevance which exists betweenpersons can be determined properly.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a whole configuration of an information system 10;

FIG. 2 shows an example of a text database 20.

FIG. 3 shows a functional configuration of an evaluation system 30;

FIG. 4 shows an example of a data structure of a storing means 310;

FIG. 5 shows an example of a process for evaluating relevance betweenpersons by the evaluation system 30;

FIG. 6 shows an example of an evaluated relevance by the evaluationsystem 30; and

FIG. 7 shows an example of a hardware configuration of an informationprocessing apparatus 400 which serves as the evaluation system 30.

DETAILED DESCRIPTION OF THE INVENTION

Hereinafter, the present invention is described through an embodiment ofthe present invention. The embodiment described below does not limit thescope of claims, nor may all the combinations of the characteristicsdescribed in the embodiment always be necessary as means for solvingproblems of the present invention.

FIG. 1 shows a whole configuration of the information processing system10. The information processing system 10 includes a text database 20 andan evaluation system 30. The text database 20 stores a plurality oftexts in each of which evaluations or feelings of a person as a targetto another person are expressed. This text may further store informationabout a fact that the person and another person acted together, or anexpression the person and the another person share. The evaluationsystem 30 evaluates directed relevance and/or undirected relevancebetween the person and another person based on a text stored in the textdatabase 20.

FIG. 2 shows a specific example of the text database 20. The textdatabase 20 includes a plurality of texts, for example, a text 200-1through a text 200-N. The text stored in the text database 20 may bestandard data complying with a certain format, or nonstandard data suchas a memo, an electronic mail, and the like. The standard text is shownas an example in FIG. 2. A salesman of an imaginary company recordsinformation obtained from his client as the text 200-1 according to apredetermined format. The example of FIG. 2 shows that a client namedKoji Yamamoto, the president of XYZ Electric Company, had a talk withPresident Yamaguchi of ABC Company, about their hobby, golf, for aninterview with a magazine of business world. The example of FIG. 2further shows that this information was collected on 21st of Jul. 2005.

As described above, the text 200-1 may include the expression of a factthat a person acted together with another person, such as an expression,“had a talk”. The text 200-1 may also includes expressions of someone'sfeeling toward another person, such as “be close with (be in goodterm)”, and the like. The evaluation system 30 according to the presentembodiment evaluates relevance between persons based on the expressions.Thereby, the evaluation system 30 also aims to properly evaluatedirected relevance, such as a case in which a person and another persontrust each other, as well as a case in which a person respects anotherperson unilaterally, without reciprocation. Furthermore, the evaluationsystem 30 also aims to properly evaluate a situation which should not beutilized, such as a case in which a person bears negative feelingstoward another person, or the like.

FIG. 3 shows a functional configuration of the evaluation system 30. Theevaluation system 30 includes relevance detecting means 300, storingmeans 310, attribute detecting means 320, evaluating means 330 andoutputting means 340. The relevance detecting means 300 detects directedrelevance of a person to another person and/or undirected relevancebased on the texts stored in the text database 20. More specifically,the relevance detecting means 300 detects person's names from the texts.Then, for every person of the detected person's names, the relevancedetecting means 300 detects another person who appears along with theformer person in the same text. Then, the relevance detecting means 300detects an expression indicating such relevance in the text in which thenames are found.

Firstly, this expression is evaluations or feelings of a person as atarget to another person. For example, expressions of feelings may be“like”, “trust”, “respect”, “appreciate”, “obliged to”, and the like.Also, expressions of evaluations can be not only general evaluationssuch as “be good at one's job” or “good personality” but alsoevaluations concerning specific information, such as “familiar withscientific technology”, “familiar with the stock market” and the like.In this case, the relevance detecting means 300 can detect evaluationsassociated with a specific field.

When the expression of evaluations or feelings of a person as a targetby another person is detected, then the relevance detecting means 300determines that directed relevance from the person to the another personexists. That is, for example, when the expression that a person Arespects a person B is detected, the relevance detecting means 30determines that directive relevance from the person A to the person Bexists. As the above-mentioned data showing the directed relevance, therelevance detection means 300 may create a directed graph in which aperson is indicated as a node and relevance is indicated as an edge. Anexample of this will be explained in FIG. 6.

Also, the relevance detecting means 300 may detects undirected relevancebetween a person and another person based on a text in which the factthat the person and another person acted together or information thatthe person and another person share is described. That is, for example,when the expression indicating that a person A and a person B had a talkis detected, the relevance detecting means 30 determines that undirectedrelevance between the person A and the person B exists. As theabove-mentioned data show undirected relevance, the relevance detectionmeans 300 may create an undirected graph in which a person is indicatedas a node and relevance is indicated as an edge. The undirected graphcan be created by adding an undirected edge to the above mentioneddirected graph.

Also, the relevance detecting means 300 may further detect a weightindicating the strength of relevance based on the frequency with whichevaluations or feelings are expressed. More specifically, it means that,when evaluations or feelings are frequently expressed in the textdatabase 20, the relevance detecting means 300 evaluates that therelevance based on the expressions or the feelings is strong compared tothe case in which the expressions or feelings are not frequentlyexpressed in the text database 20. Also, the relevance detecting means300 may evaluate a weight indicating the strength of the relevance basedon the date when the evaluation or feeling is expressed. Morespecifically, it means that, if the evaluation or the feeling wasexpressed recently, the relevance detecting means 300 evaluates therelevance based on the expression as strong compared to the case inwhich the evaluation or the feeling was expressed a long time ago.

The storing means 310 stores information on the relevance detected bythe relevance detecting means 300 and its weight, and provides theinformation to the evaluating means 300. Also, the storing means 310stores the relevance between each of the attribute values and each ofthe other attribute values of a person in advance. For example, anattribute of a person can be an organization to which persons belong. Inthis case, the attribute value shows identification information such asthe name of the organization, and the like. That is, for example, thestoring means 310 stores information, as relevance, such as the factthat ABC Company and XYZ Electric Company are competing, the fact thatthey are in business tieup, and the like. Furthermore, the storing means310 may store the relevance of the attribute value by associating themwith the time at which the relevance is evaluated.

The attribute detecting means 320 detects the attributes described inthe text stored in the text database 20, for each of two persons. Theevaluating means 330 evaluates the relevance between a first person anda second person to be evaluated, based on the relevance detected by therelevance detecting means 300. More specifically, firstly the evaluatingmeans 330 selects a plurality of relevances which start from the firstperson and reach the second person, via at least one further person. Theplurality of relevances include the relevances which are detected by therelevance detecting means 300 and stored in the storing means 310. Theevaluating means 330 evaluates the relevances between the first personand the second person based on the plurality of selected relevances. Forexample, when the relevances indicate a positive evaluation or feeling,and the relevances are shown as a directed graph, the evaluating means330 may evaluate the relevance between the first person and the secondperson based on the plurality of relevances on a path reverselyfollowing the directed graph. Also, when the weight of the relevance isdetected, the evaluating means 330 may evaluate the relevances furtherbased on the weight of the relevances. Also, the evaluating means 330may evaluate the relevances of the persons based on the attributesdetected for each person and the relevance between these attributes.

Incidentally, instead of relevance between persons described above, thetarget of evaluation for the evaluating means 330 may be relevancebetween organizations. More specifically, the relevance detecting means330 detects directed relevance of an organization as a target to anotherorganization based on a text in which evaluations and feelings of theorganization by the another organization. For example, the text includesnot only statements, press reports, and the like, released by anorganization, but also remarks of the representative of an organizationwhen the organization is a company, and the like. The evaluating means330 then evaluates, with respect to a set of a first organization and asecond organization to be evaluated, relevance between the firstorganization and the second organization based on a plurality ofrelevances including the detected relevances and reaching the secondorganization from the first organization via at least one furtherorganization. Thus, the evaluation system 30 according to the presentembodiment can include, as a target of evaluation, not only persons, butalso subjects, such as organizations like companies, which can indicateevaluations or feelings in a text.

The outputting means 340 outputs the relevance evaluated by theevaluating means 330. Also, the outputting means 340 performs outputtingbased on the relevance. For example, the outputting means 340 may outputa person on a path reversely following the directed relevances from thefirst person to the second person, as an introducer, who can introducethe first person to the second person. The path can include undirectedrelevance. Therefore, it is possible to support sales activityeffectively by using personal connections. That is, when a person ishoping to sell goods or services to a person A, it is possible toadvance sales activity smoothly by selecting a person B, as anintroducer, whom the person A trusts.

FIG. 4 shows an example of a data structure of the storing means 310.Also, the storing means 310 stores the relevance between each of theattribute values and each of another attribute values in advance. Forexample, the storing means 310 stores 0.5 as the weight of relevanceregarding the set of ABC Company, which is a first attribute value, andXYZ Electric Company, which is a second attribute value. If thisrelevance shows a friendship between companies, it is considered thatthere is a good friendship between ABC Company and XYZ Electric Companyto a certain degree as the weight of +0.5 is a positive value. Also, thestoring means 310 stores the relevance of the attribute values byassociating them with the time when the relevance was evaluated. Forexample, the example of FIG. 4 shows that the relevance between ABCCompany and XYZ Electric Company was evaluated on 25th of Apr. 2005. Thedate of the evaluation may be the date when the information about therelevance is inputted into the storing means 310, or the date when thetext about the relevance is created.

FIG. 5 shows an example of a process for evaluating the relevancebetween persons by the evaluation system 30. The relevance detectingmeans 300 acquires a text from the text database 20 (S500). Therelevance detecting means 300 detects person's names in the acquiredtext (S510). For every person of the detected person's names, therelevance detecting means 300 detects another person who appears alongwith the former person in the same text, and further detects expressionsindicating the relevance between two persons (S520). Then, the relevancedetecting means 300 detects directed relevance and/or undirectedrelevance from the person to the other person by using theseexpressions. The attribute detecting means 320 detects the attributesincluded in the text stored in the text database 20 for each person(S530).

The evaluating means 330 evaluates, with respect to a set of a firstperson and a second person to be evaluated, relevance between the firstperson and the second person based on the information detected by therelevance detecting means 300 (S540). An example of evaluated relevancewill be explained with reference to FIG. 6. FIG. 6 shows an example ofrelevance evaluated by the evaluation system 30. In FIG. 6, eachrectangular area indicates a node showing a person, an edge having anarrow at one end only indicates a directed edge, and an edge havingarrows at opposite ends indicates an undirected edge.

For example, firstly, the evaluating means 330 selects a plurality ofrelevances which start from Manager Abe and reach Koji Yamamoto via atleast one further person. For example, the evaluating means 330 selectsa positive relevance with a weight of 0.2 and a positive relevance witha weight of 0.5, in a path from Manager Abe to Koji Yamamoto viaPresident Yamaguchi. On the other hand, the evaluating means 330 selectsa positive relevance with a weight 0.8 and a negative relevance with aweight of 0.5, in a path from Manager Abe to Koji Yamamoto via SenichiHoshino. These selected relevances include relevances detected by therelevance detecting means 300. That is, for example, the directedrelevance from Koji Yamamoto to President Yamaguchi may be detected as aresult of a text including expressions of positive feelings orevaluations from Koji Yamamoto toward President Yamaguchi beingdetected.

Next, the evaluating means 330 evaluates the relevance between ManagerAbe and Koji Yamamoto based on these selected relevances. Morespecifically, the evaluating means 330 may evaluate the total values orthe average values of these relevances as the values of the relevancebetween Manager Abe and Koji Yamamoto. That is, the evaluating means 330may evaluate the path of the relevance via President Yamaguchi as 0.7,which is calculated by 0.5+0.2, and the path of the relevance viaSenichi Hoshino as 0.3, which is calculated by 0.8+(−0.5). According tothe evaluated relevance, it is preferable for Manager Abe to contactKoji Yamamoto via President Yamaguchi, rather than via Senichi Hoshino,for the sales strategy.

Also, the evaluating means 330 may select a plurality of relevancesincluding relevances between attribute values, in paths which start fromManager Abe via its attribute value and reaches an attribute of KojiYamamoto. For example, the evaluating means 330 selects the relevancepath which starts from GDG Communication, which is an affiliationorganization of Manager Abe, and reaches ABC Company, which is anaffiliation organization of Koji Yamamoto. That is, the evaluating means330 selects the positive relevance path with a weight of 0.4 in therelevance between GDG Communication and XYZ Electric Company, and anegative relevance path with a weight of 1.0 between XYZ ElectricCompany and ABC Company. Then the evaluating means 330 may evaluate thetotal value of the weights (that is −0.6) as the evaluation of therelevance between Manager Abe and Koji Yamamoto. Thus, the evaluatingmeans 330 may evaluate the relevance between the attribute values of afirst person and a second person more highly when the weight of therelevance is large, compared to the case in which the value of theweight of the relevance between the first person and the second personis small.

In the above described process, the weights of a plurality of differentrelevances may be evaluated for a set of common persons. For example, asto the weight of the relevance between Koji Yamamoto and Manager Abe viaPresident Yamaguchi, evaluations are +0.7 based on the personalrelevance, and −0.6 based on the affiliation relevance. In this case,for example, the evaluating means 330 may select the smaller value ofthe weight as the result of the evaluation of the relevance. Thereby, itis possible to eliminate a risk of failing in sales activity by usingthe information about the relevance carefully.

Also, when evaluating the relevance by using attribute values, it isdesirable to use the time of evaluation and the property of theevaluation. For example, when the relevance between the attribute of afirst person and the attribute of a second person was evaluatedrecently, the evaluating means 330 may evaluate the relevance betweenthe first person and the second person more highly, compared to the casein which the time of the evaluation is old. The time of the evaluationcan be obtained from the information stored in the storing means 310shown in FIG. 4. Also, when the attribute shows the organization towhich they belong, the evaluating means 330 may evaluate more highly ifthe size of the organization is large, compared to the case in which theorganization is smaller. The size of the organization is obtained fromthe number of links between the attribute values of the organization andthe nodes indicating persons.

According to the above-mentioned example, it is possible to evaluate theweight of the relevance between one attribute value and anotherattribute value based not only on a text but also on the property ofeach attribute.

The outputting means 340 performs outputting based on the relevanceevaluated by the evaluating means 330 (S550). Hereinafter, four appliedexamples will be explained with reference to the example of FIG. 6.

Display of Introducer

The outputting means 340 outputs an introducer for introducing asalesman to a certain person based on the relevance. Generally, in orderto effectively conduct this kind of sales activity, it is important toselect an introducer who is trusted by the person. The outputting means340 can select such an introducer based on the relevance evaluated bythe evaluating means 330.

More specifically, firstly, it is supposed that the evaluating means 330evaluates directed relevance which shows a positive evaluation orfeeling from the person toward another person. For example, in theexample of FIG. 6, it is detected that Koji Yamamoto has a positiveevaluations or feelings toward President Yamaguchi. Then, with respectto relevances from a first person (Manager Abe) to a second person (KojiYamamoto), the evaluating means 330 reversely follows the directedrelevance or follows the undirected relevance, and selects a person onthe path reached. The evaluating means 330 then evaluates the selectedperson as an introducer, who can introduce the first person to thesecond person. That is, in this example, Senichi Hoshino and PresidentYamaguchi are evaluated as introducers. The outputting means 340 outputsthe information indicating these introducers. Preferably, the outputtingmeans 340 outputs the introducers in descending order of the weights ofpaths, where the introducers appear. For example, the outputting means340 may display President Yamaguchi, whose total relevance value is 0.7,more conspicuously than Senichi Hoshino, whose total relevance value is0.3, or the outputting means 340 may display only President Yamaguchi.

(2) Display of group: The evaluating means 330 may detect a groupconstituted by a plurality of persons who have strong connections witheach other, and the outputting means 340 may display the detected groupto a user. More specifically, in a graph setting each person as a nodeand each relevance as an edge, the evaluating means 330 may detect theplurality of persons who have strong connections with each other as agroup, by detecting strong-connection elements, deeming the weight ofthe relevance as the weight of an edge. In this case, the weight ofundirected relevance between a person and another person is assigned tothe weight of directed relevance from the person to another person, andthe weight of the directed relevance from another person to the person.This allows the existing technique for detecting strong-connectionelements from a directed graph with weights to be applicable, and it ispossible to properly detect a plurality of persons whose relevance isstrong with each other.

(3) Display of a key person: When the relevance indicates a positiveevaluation or feeling from one person toward another person, theevaluating means 330 calculates, for example, a total value or anaverage value, which are values based on the weight of the relevancefrom the another person to the person. Then, the evaluating means 330evaluates the one person as a key person in the relevance of persons ifa value based on the total value of all relevances to that person islarger than a predetermined reference value. Thereby, it is possible toproperly evaluate a person who is trusted and highly evaluated by manypersons.

(4) Sales promotion of goods, etc.: If information on the history ofpurchasing goods can be obtained as attribute information of one person,it can be seen that it is effective to use the historical informationfor the sales promotion of goods, and the like, by combining thehistorical information with the relevance between persons. Morespecifically, the outputting means 340 outputs information that goods orservices purchased by one person in the group detected in the example(2) should be recommended to the other persons in the same group.

In addition to this, it is determined that the same kind of goods orservices purchased by one person in the group may be recommended toother persons in the same group. More specifically, for example, thegoods or services of the same kind are associated with particular goodsor the services, and stored in the storing means 310 or the like. Then,the outputting means 340 selects goods or services of the same kind asthe goods or services purchased by one person in the group based on theinformation stored in the storing means 310, or the like. Then, theoutputting means 340 outputs information that the goods or servicesshould be recommended to the other persons in the group. Thus, by makinguse of the relevance between persons for sales activity, persons whohave never been considered as potential customers can be discovered aspromising targets for sales.

FIG. 7 shows an example of a hardware configuration of an informationprocessing apparatus 400 which serves as the evaluation system 30. Theinformation processing apparatus 400 includes; a CPU peripheral portionhaving CPU 1000, a RAM 1020 and a graphic controller 1075 mutuallyconnected via a host controller 1082; an input/output portion having acommunication interface 1030, a hard disk drive 1040, and a CD-ROM drive1060 connected to the host controller 1082 via an input/outputcontroller 1084; and a legacy input-output portion having a BIOS 1010, afloppy disk drive 1050, and an input/output chip 1070 connected to theinput/output controller 1084.

The host controller 1082 connects the RAM 1020 to the graphic controller1075 and the CPU 1000 which access the RAM 1020 with a high transferrate. The CPU 1000 operates based on a program stored in the BIOS 1010and the RAM 1020, and controls each part. The graphic controller 1075acquires image data generated on a frame buffer provided on the RAM 1020by the CPU 1000 and the like, and displays it on the display apparatus1080. Alternately, the graphic controller 1075 may include the framebuffer which stores the graphic data generated by the CPU 1000 and thelike.

The input/output controller 1084 connects the host controller 1082 tothe communication interface 1030, the hard disk drive 1040, and theCD-ROM drive 1060 which are relatively high-speed input/outputapparatuses. The communication interface 1030 communicates with externalapparatuses via a network. The hard disk drive 1040 stores a program anddata used by the information processing apparatus 400. The CD-ROM drive1060 reads out programs or data from a CD-ROM 1095, and offers it to theRAM 1020 or the hard disk drive 1040.

Also, the input/output controller 1084 is connected to relativelylow-speed input/output apparatuses such as the BIOS 1010, the floppydisk drive 1050, the input/output chip 1070, and the like. The BIOS 1010stores a boot program performed by the CPU 1000 during start of up theinformation processing apparatus 400, a program depending on thehardware of the information processing apparatus 400, and the like. Thefloppy disk drive 1050 reads out a program or data from a floppy disk1090, and offers it to the RAM 1020 or the hard disk drive 1040 via theinput/output chip 1070. The input/output chip 1070 connects variousinput/output apparatuses via the floppy disk 1090, or interfaces such asa parallel port, serial port, keyboard port, mouse port, and the like.

A program provided to the information processing apparatus 400 is storedin a recording medium such as the floppy disk 1090, a CD-ROM 1095, an ICcard, or the like, and provided by the user. The program is read outfrom the recording medium via the input/output chip 1070 and/or theinput/output controller 1084, installed on the information processingapparatus 400 to be performed. The operation of the informationprocessing apparatus 400 caused by the program is the same as theoperations of the evaluation system 30 described in FIG. 1 to FIG. 6,and thus the explanation is omitted.

The program described above may be stored in an external storage medium.As the storage medium, not only the floppy disk 1090, the CD-ROM 1095,but also an optical recording medium such as a DVD, a PD, and the like,and a semiconductor memory such as a tape medium, an IC card, and thelike, may be used. Also, a storage apparatus such as a hard disk or RAMprovided in a server system connected to a dedicated communicationnetwork or the internet may be used as a recording medium in order toprovide to a program to the information processing apparatus 400 via anetwork.

Since the present invention is explained by using the embodimentdescribed above, it should be noted here that the technical scope of thepresent invention is not limited to the above embodiment. For thoseskilled in the art, it is assumed that the various modifications andimprovements may be included in the above embodiments. Also, from thescope of the claims, it is also assumed that those alternation andimprovements to the embodiment of the invention may be included in thetechnical scope of the present invention.

1. A program for operating an information processing apparatus tofunction as a system for evaluating relevance between persons, theprogram operating the information processing apparatus to function as:relevance detecting means for detecting directed relevance of a personas a target to another person based on a text in which evaluations orfeelings of the person by another person are expressed; storing meansfor storing the detected relevance; evaluating means for evaluating,with respect to a set of a first person and a second person to beevaluated, relevance between the first person and the second personbased on a plurality of relevances including the relevances stored inthe storing means and reaching the second person from the first personvia at least one further person; and outputting means for outputting theevaluated relevance.
 2. The program according to claim 1, wherein therelevance detecting means further detects a weight indicating a strengthof the relevance based on frequency in which the evaluations or thefeelings are expressed in the text, and/or a time when the evaluationsor the feelings are expressed in the text; and the evaluating meansfurther evaluates the relevance between the first person and the secondperson based on the detected weight.
 3. The program according to claim2, wherein if the evaluations or the feelings are expressed, therelevance detecting means detects the strength of the relevance as apositive weight, and if the evaluations or the feelings are expressed inreverse to the afore-mentioned evaluations or the feelings, therelevance detecting means detects the strength of the relevance as anegative weight.
 4. The program according to claim 2, wherein therelevance detecting means further detects undirected relevance between aperson and another person based on the text in which a fact that theperson and the another person acted together, or information that theperson and the another person share is expressed; the evaluating meansfurther evaluates the relevance between the person and the anotherperson based on the undirected relevance detected.
 5. The programaccording to claim 4, wherein in the case in which the directedrelevance shows a positive evaluation or feeling from a person toanother person, the evaluating means evaluates a person on pathsreversely following the directed relevances from the first person to thesecond person, as an introducer, who can introduce the first person tothe second person.
 6. The program according to claim 5, wherein theoutputting means further outputs the introducers in descending order ofweights of the relevances in the path in which the introducer exists. 7.The program according to claim 4, wherein the evaluating means furtherdetects strongly-connected components of a directed graph settingrespective persons as nodes and the relevances as weighted edges, anddetects a set of nodes included in the detected strongly-connectedcomponents as a group by a plurality of persons, by further assigningthe weights of the undirected relevance between a person and anotherperson to the weights of directed relevances from the person to theanother person, and the weight of the directed relevance from anotherperson to the person.
 8. The program according to claim 4, wherein inthe case in which the relevance shows a positive evaluation or feelingfrom the person to the another person, the evaluating means furtherevaluates the person as a key person in the human relationship under acondition that a value based on a total amount of the weights of therelevances from the another person to the person is larger than apredetermined reference value.
 9. The program according to claim 4,wherein the program operates the information processing apparatus tofurther function as attribute detecting means for detecting attributesfor respective persons expressed in the text; the storing means storesrelevance between each of a plurality of attributes and each of anotherattributes, and in the case in which the directed relevance shows apositive evaluation or feeling from the one person to the anotherperson, the evaluating means evaluates the weight of the relevancebetween the first person and the second person more highly when theweight of the relevance between the attribute value of the first personand the attribute value of the second person is larger, compared to thecase in which the weight of the relevance between the first person andthe second person is smaller.
 10. The program according to claim 9,wherein the storing means stores the relevance of the attribute valuesby associating the time when the relevances were evaluated, and theevaluating means evaluates the weight of the relevance between the firstperson and the second person more highly in the case in which therelevance between the attribute of the first person and the attribute ofthe second person were evaluated recently, compared to the case in whichthe time of the evaluation is old.
 11. The program according to claim10, wherein in the case in which the attribute indicates an affiliationorganization, the evaluating means evaluates the weight of the relevancebased on the attribute of the person and the attribute the anotherperson more highly when the affiliation organization is bigger, comparedto the case in which the affiliation organization is smaller.
 12. Theprogram according to claim 10, wherein the evaluating means detectsstrongly connected components of a graph setting respective persons asnodes and the relevances as edges, and detects a set of nodes includedin the detected strongly-connected components as a group consisting ofmultiple persons; and in the case in which the attribute indicates anarticle or a service purchased by a person, the outputting means outputsinformation to recommend an article or a service purchased by a personin the group to another person in the same group.
 13. The programaccording to claim 12, wherein the storing means stores the article orthe service of the same kind associated with each of the article or theservice; and the outputting means outputs information to recommend anarticle or a service purchased by the one person in the group to theanother persons in the group.
 14. A method for evaluating relevancebetween persons, comprising: step of detecting directed relevance of aperson as a target to another person based on a text in whichevaluations or feelings of the person by another person are expressed,and step of evaluating, with respect to a set of a first person and asecond person to be evaluated, relevance between the first person andthe second person based on a plurality of relevances including thedetected relevances and reaching the second person from the first personvia at least one further person.
 15. The method according to claim 14,wherein in the step of detecting the relevance, a weight indicating astrength of the relevance is further detected based on frequency inwhich the evaluations or the feelings are expressed in the text, and/ora time when the evaluations or the feelings are expressed in the text;and in the step of evaluating, the relevance between the first personand the second person is further evaluated based on the detected weight.16. The method according to claim 15, wherein in the step of detectingthe relevance, in the case in which the evaluation or the feeling isexpressed, the strength of the relevance as a positive weight isdetected, and in the case in which the evaluation or the feeling isexpressed in reverse to the afore-mentioned evaluation or the feeling,the strength of the relevance as a negative weight is detected.
 17. Themethod according to claim 15, wherein in the step of detecting therelevance, undirected relevance between a person and another person isfurther detected based on the text in which a fact that the person andthe another person acted together, or information that the person andthe another person share is expressed; and in the step of evaluating therelevance, the relevance between the one person and the another personis further evaluated based on the undirected relevance detected.
 18. Themethod according to claim 17, wherein in the case in which the directedrelevance shows a positive evaluation or feeling from one person toanother person; in the step of evaluating the relevance, a person on apath reversely tracing the directed relevances from the first person tothe second person is evaluated, as an introducer, who can introduce thefirst person to the second person.
 19. A system for evaluating relevancebetween persons, comprising: relevance detecting means for detectingdirected relevance of a person as a target by another person based on atext in which evaluations or feelings of the person to another personare expressed, and evaluating means for evaluating, with respect to aset of a first person and a second person to be evaluated, relevancebetween the first person and the second person based on a plurality ofrelevances including the detected relevances and reaching the secondperson from the first person via at least one further person.
 20. Aprogram for operating an information processing apparatus to function asa system for evaluating relevance between organizations, the programoperating the information processing apparatus to function as: relevancedetecting means for detecting relevance of an organization as a targetby another organization based on a text in which evaluations or feelingsof the organization to another organization are expressed; andevaluating means for evaluating, with respect to a set of a firstorganization and a second organization to be evaluated, relevancebetween the first organization and the second organization based on aplurality of relevances including the detected relevances and reachingthe second organization from the first organization via at least onefurther organization.